Recoverability analysis for modified compressive sensing with partially known support.

The recently proposed modified-compressive sensing (modified-CS), which utilizes the partially known support as prior knowledge, significantly improves the performance of recovering sparse signals. However, modified-CS depends heavily on the reliability of the known support. An important problem, wh...

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Autores principales:	Jun Zhang, Yuanqing Li, Zhenghui Gu, Zhu Liang Yu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/111f48327ab14713be1e2f5a69e785d2
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spelling	oai:doaj.org-article:111f48327ab14713be1e2f5a69e785d22021-11-18T08:33:12ZRecoverability analysis for modified compressive sensing with partially known support.1932-620310.1371/journal.pone.0087985https://doaj.org/article/111f48327ab14713be1e2f5a69e785d22014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24520341/?tool=EBIhttps://doaj.org/toc/1932-6203The recently proposed modified-compressive sensing (modified-CS), which utilizes the partially known support as prior knowledge, significantly improves the performance of recovering sparse signals. However, modified-CS depends heavily on the reliability of the known support. An important problem, which must be studied further, is the recoverability of modified-CS when the known support contains a number of errors. In this letter, we analyze the recoverability of modified-CS in a stochastic framework. A sufficient and necessary condition is established for exact recovery of a sparse signal. Utilizing this condition, the recovery probability that reflects the recoverability of modified-CS can be computed explicitly for a sparse signal with [Formula: see text] nonzero entries. Simulation experiments have been carried out to validate our theoretical results.Jun ZhangYuanqing LiZhenghui GuZhu Liang YuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e87985 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jun Zhang Yuanqing Li Zhenghui Gu Zhu Liang Yu Recoverability analysis for modified compressive sensing with partially known support.
description	The recently proposed modified-compressive sensing (modified-CS), which utilizes the partially known support as prior knowledge, significantly improves the performance of recovering sparse signals. However, modified-CS depends heavily on the reliability of the known support. An important problem, which must be studied further, is the recoverability of modified-CS when the known support contains a number of errors. In this letter, we analyze the recoverability of modified-CS in a stochastic framework. A sufficient and necessary condition is established for exact recovery of a sparse signal. Utilizing this condition, the recovery probability that reflects the recoverability of modified-CS can be computed explicitly for a sparse signal with [Formula: see text] nonzero entries. Simulation experiments have been carried out to validate our theoretical results.
format	article
author	Jun Zhang Yuanqing Li Zhenghui Gu Zhu Liang Yu
author_facet	Jun Zhang Yuanqing Li Zhenghui Gu Zhu Liang Yu
author_sort	Jun Zhang
title	Recoverability analysis for modified compressive sensing with partially known support.
title_short	Recoverability analysis for modified compressive sensing with partially known support.
title_full	Recoverability analysis for modified compressive sensing with partially known support.
title_fullStr	Recoverability analysis for modified compressive sensing with partially known support.
title_full_unstemmed	Recoverability analysis for modified compressive sensing with partially known support.
title_sort	recoverability analysis for modified compressive sensing with partially known support.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/111f48327ab14713be1e2f5a69e785d2
work_keys_str_mv	AT junzhang recoverabilityanalysisformodifiedcompressivesensingwithpartiallyknownsupport AT yuanqingli recoverabilityanalysisformodifiedcompressivesensingwithpartiallyknownsupport AT zhenghuigu recoverabilityanalysisformodifiedcompressivesensingwithpartiallyknownsupport AT zhuliangyu recoverabilityanalysisformodifiedcompressivesensingwithpartiallyknownsupport
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Recoverability analysis for modified compressive sensing with partially known support.

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